Performance evaluation of classification algorithms by k-fold and leave-one-out cross validation

Classification is an essential task for predicting the class values of new instances. Both k-fold and leave-one-out cross validation are very popular for evaluating the performance of classification algorithms. Many data mining literatures introduce the operations for these two kinds of cross valida...

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Veröffentlicht in:	Pattern recognition Jg. 48; H. 9; S. 2839 - 2846
1. Verfasser:	Wong, Tzu-Tsung
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.09.2015
Schlagworte:	Classification Independence k-Fold cross validation Leave-one-out cross validation Sampling distribution k-Fold cross validation Classification Independence Leave-one-out cross validation Sampling distribution
ISSN:	0031-3203, 1873-5142
Online-Zugang:	Volltext
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